Product Manager, Governance Risk and Compliance Tooling

Google Google · Big Tech · Austin, TX +1

Product Manager for Governance Risk and Compliance (GRC) tooling and infrastructure team, focusing on integrating AI/ML capabilities into GRC infrastructure to automate risk assessments and compliance monitoring. The role involves defining product strategy, managing the full product lifecycle, and partnering with engineering, data science, legal, and privacy stakeholders to deliver AI-first solutions.

What you'd actually do

  1. Define and lead the product idea for integrating AI/ML capabilities into GRC infrastructure (e.g., automated document classification, LLM-based risk summarization, and predictive risk scoring).
  2. Drive the development of scalable backend services and tooling that support the TRM organization’s data ingestion, risk engine, and reporting needs.
  3. Manage the entire product lifecycle from ideation to launch, including writing detailed PRDs, managing backlogs, and defining success metrics.
  4. Work closely with Risk and Compliance practitioners to translate their domain expertise into technical requirements.
  5. Partner with engineering and data science teams to prioritize high-impact AI features while ensuring data privacy and ethical AI standards are maintained.

Skills

Required

  • technical product management
  • taking software products through a full lifecycle
  • taking technical products from conception to launch
  • building or implementing AI/ML-driven features or infrastructure
  • working with LLMs
  • NLP
  • data pipelines

Nice to have

  • prompt engineering
  • model evaluation
  • deploying AI solutions in a corporate/enterprise environment
  • Risk Management
  • Compliance
  • Security
  • Governance (GRC) technology
  • use data to justify product decisions
  • measure the efficiency gains of automated workflows
  • communicate complex technical concepts to non-technical stakeholders

What the JD emphasized

  • AI/ML capabilities
  • AI-first
  • generative AI and machine learning
  • automated processes
  • AI/ML capabilities
  • LLM-based risk summarization
  • predictive risk scoring
  • AI features
  • ethical AI standards
  • AI/ML-driven features or infrastructure
  • LLMs
  • NLP
  • data pipelines
  • prompt engineering
  • model evaluation
  • deploying AI solutions

Other signals

  • integrating AI/ML capabilities into GRC infrastructure
  • leveraging generative AI and machine learning to transform manual risk workflows into automated processes
  • AI-first